Generating digital reconstructions of real-world, three-dimensional (3D) vehicle events by conventional means is often a time-consuming, expensive, and difficult process. First, it often relies on the collection of high-fidelity 3D data that can be difficult and expensive to obtain, due to the high cost of and low availability of the knowhow to operate the requisite sensors. Second, due to the difficulty and expense of obtaining such data, it is often impossible or impractical to deploy such detection at scale and thus existing solutions can fail to adequately capture, map, or analyze edge cases (e.g., rare events), which can be especially desirable to obtain (e.g., for development of robust control algorithms). Furthermore, many conventional methods for reconstructing 3D environments can be labor intensive, often work only in specific or specialized contexts, and can produce reconstructed geometry that contains undesirable defects, among other disadvantages.
Thus, there is a need in the digital mapping field to create a new and useful system and method for environmental reconstruction and analysis. This invention provides such new and useful system and method.